Method for digitally magnifying images

ABSTRACT

A method for digitally magnifying images applied to an electronic device includes the steps of: reading in a preview image inputted into the electronic device; executing a 2-fold image magnifying process to the preview image; executing a fuzziness removing process to the preview image; segmenting the preview image into a background area and a text area, executing a correspondingly text strengthening process to the text area; and determining if the preview image is magnified up to a predetermined amplification factor; if yes, outputting the preview image after being magnified to a display screen for displaying the preview image; and otherwise, going back to re-execute the 2-fold image magnifying process to the magnified preview image, and then executing the fuzziness removing process and the text strengthening process, in order to generate the preview image magnified about 4-fold or more.

FIELD OF THE INVENTION

The present invention relates to a method for magnifying images, andmore particularly to a method for digitally magnifying images applied toan electronic device having an image capturing element so as toefficiently remove the unclear and shaking problems of images, which arecaptured and digitally magnified by the electronic device, caused byhigh-speed moving and vibrating of the image capturing element, to lowerthe interference of random noise signals, and to provide more stable andclearer images.

BACKGROUND OF THE INVENTION

Presently, with the advance of medical technologies and the improvementof life qualities, human life spans are increasingly elongated,resulting in serious problems relating to aging society. Especially,with the increase of age, when one reaches such as 40 years old or more,the presbyopic problem will be gradually apparent. Thus, a magnifier ora pair of presbyopic glasses (i.e. reading glasses) is an essentiallyimportant tool for him to read books or letters, browse homepages, orview a display screen in a short distance. Otherwise, the deteriorationof eyesight may cause the fatigue of eyes, resulting in effecting one'sworking efficiency. Moreover, the dim eyesight may cause a faintdiscomfort, resulting in effecting the quality of one's daily life.

Recently, with the advance of digital photography, various electronicdevices (such as digital cameras, digital video cameras, notebookcomputers, mobile phones, and PDAs) provided with a digital imagecapturing element (such as a CCD or CMOS) are continuously developed,wherein the image quality of the digital image capturing element iscontinuously enhanced, the entire volume of the electronic device iscontinuously miniaturized, and the selling price thereof is continuouslylowered down, so that it is advantageous to increase the market share ofthe electronic devices provided with the digital image capturingelement. In consideration of the increasing trend of middle ages and oldages, it is necessary to consider the possible problems, which themiddle ages and the old ages may face, as an important factor whenmanufacturers design and develop the electronic devices, in order tosatisfy the needs of different ages.

For example, referring now to FIG. 1, a traditional digital magnifierwhich is commercially available and portable is illustrated, wherein thedigital magnifier designated by numeral 10 has a size similar to anormal computer mouse, and is provided with an image capturing element(such as a CCD or CMOS, as shown in FIG. 1). The image capturing elementof the digital magnifier 10 can be used to capture a preview image (suchas a text image of a book or a magazine 12), magnify the captured image,and transmit the magnified image into a terminal apparatus 11 (such as apersonal computer or a television) connected to the digital magnifier10. Then, the terminal apparatus 11 displays the content of themagnified image. However, the digital magnifier 10 is not onlyexpensive, but also has a volume greater than that of a traditionalmagnifier or traditional presbyopic glasses. When the digital magnifier10 is used, it must be connected to the terminal apparatus 11, resultingin inconvenient usage. Hence, many old ages affording the digitalmagnifier 10 may still select to directly hang the traditionalpresbyopic glasses or the traditional magnifier on his/her neck forconvenient usage, if necessary. As described above, although thecommercially-available portable digital magnifier 10 has more and betterfunctions, the digital magnifier 10 still can not satisfy actual needsof general middle ages and old ages. As a result, it is an importantsubject for related design houses and manufacturers of variouselectronic devices to think how to develop a portable electronic deviceto replace the traditional presbyopic glasses or the traditionalmagnifier whereby the middle ages and the old ages having the presbyopicproblem read books or letters, browse homepages, or view a displayscreen can directly and conveniently read an magnified text image.

In addition, due to the improvements of text and figure recognitiontechnologies in recent years, various electronic devices installed witha text and figure recognition software are continuously developed, inorder to satisfy the needs of different consumers. As to traditionalrecognition software installed in commercially-available opticalcharacter recognition (OCR) devices, bar code recognition (BCR) devices,or business card recognition (Biz card) devices, text recognitionsoftware seriously demands the quality of inputted images while bar coderecognition software and business card recognition software are verysensitive to the size of inputted text images. If the size of textimages is smaller than a predetermined size value, the recognition ratethereof will be substantially lowered down to the situation that even noany text image can be recognized. Moreover, the traditional bar coderecognition software also seriously demands the minimum width, height,and pitch of bar codes. If an inputted image of a bar code can not fitthe foregoing demands, the recognition rate thereof will besubstantially lowered down to the situation that even no bar code can berecognized. Furthermore, it is not ensured that an image captured by animage capturing element of the traditional recognition device can alwaysfit the demands of the recognition software of the traditionalrecognition device, while the captured image generally includes variousnoise signals, resulting in lowering the recognition rate. Therefore, itis an important subject for related design houses and manufacturers ofvarious electronic devices to think how to efficiently remove the noisesignals existing in the captured image, in order to provide ahigh-quality image that is easy to be recognized by the recognitionsoftware.

It is therefore tried by the inventor to develop a method for digitallymagnifying images to solve the problems existing in the traditionalmethod for digitally magnifying images, wherein the differencetherebetween is to execute a video stabilizing process, a noise signalremoving process, a fuzziness removing process, and a text strengtheningprocess to images during image magnification, so that the processedimages will be clearer for facile reading or suitably used to otherapplications.

SUMMARY OF THE INVENTION

A primary object of the present invention is to provide a method fordigitally magnifying images, which is applied to an electronic devicecomprising or connected to an image capturing element, so that theelectronic device can execute a video stabilizing process to a previewimage real-time inputted by the image capturing element, calculate themotion of the image capturing element according to a plurality ofreal-time inputted preview images, and execute a fitting process to thecurrent preview image and the plural previous preview images, so as toefficiently remove the unclear and shaking problems of images caused byhigh-speed moving and vibrating of the image capturing element, and tolower the interference of random noise signals, for the purpose ofproviding more stable and clearer images.

A secondary object of the present invention is to provide a method fordigitally magnifying images, which is used to execute a noise signalevaluating process to the preview image by the electronic device afterexecuting the video stabilizing process, so that the preview image canbe segmented into a text area and a background area, in order todynamically evaluate a distribution range of noise signals according toa segmentation result of the text area and the background area.

A third object of the present invention is to provide a method fordigitally magnifying images, which is used to execute an imagemagnifying process to the preview image by the electronic device afterexecuting the noise signal evaluating process, wherein the preview imagecan be magnified about 2-fold according to an anti-aliased fast doubleamplification algorithm, in order to prevent from the aliasing problemof edges of the texts.

A fourth object of the present invention is to provide a method fordigitally magnifying images, which is used to execute a noise signalremoving process to the preview image by the electronic device afterexecuting the image magnifying process, wherein when background noisesignals of the preview image is removed, character points of texts (suchas the point of English letter “i”) can be efficiently protected frombeing removed.

A fifth object of the present invention is to provide a method fordigitally magnifying images, which is used to execute a fuzzinessremoving process to the preview image by the electronic device afterexecuting the noise signal removing process, wherein the preview imageis processed by a fuzzy kernel template according to a fastdeconvolution algorithm, in order to prevent from the fuzzy problem ofthe edges of the texts caused by inaccurately focusing of the imagecapturing element and magnifying the texts. Meanwhile, the fastdeconvolution algorithm is speeded up according to an integral imagemeans, so that the electronic device can provide a speed high enough toimmediately finish the image magnifying process.

A sixth object of the present invention is to provide a method fordigitally magnifying images, which is used to execute a partial textstrengthening process to the preview image by the electronic deviceafter executing the fuzziness removing process, wherein the previewimage is segmented into a background area and a text area according to aperipherally statistic data of a text, and the text area iscorrespondingly strengthened based on a dynamic threshold value, so thata text content of the preview image inputted after being magnified2-fold will be sharper and the edges of the texts will be smoother.

A seventh object of the present invention is to provide a method fordigitally magnifying images, which is selectively used to re-execute theforegoing processes to the preview image according to actual needs afterthe preview image is magnified 2-fold, wherein the foregoing processescomprise the 2-fold image magnifying process, the noise signal removingprocess, the image fuzziness removing process, and the partial textstrengthening process, so as to output a 4-fold or higher-fold previewimage. As a result, the method of the present invention can not onlyprovide a function of a digital magnifier, but also efficiently reduceor remove various interference factors (such as vibrations, noisesignals, uneven illumination, inaccurate focusing, fuzziness, etc.), sothat the magnified text images will provide more stable and clearervisual effect.

BRIEF DESCRIPTION OF THE DRAWINGS

The structure and the technical means adopted by the present inventionto achieve the above and other objects can be best understood byreferring to the following detailed description of the preferredembodiments and the accompanying drawings, wherein

FIG. 1 is an operational view of a traditional digital magnifier;

FIG. 2 is a top view of an original text image before being magnified;

FIG. 3 is a top view of the text image of FIG. 2 after being magnified2-fold by the traditional digital magnifier of FIG. 1;

FIG. 4 is a top view of the text image of FIG. 2 after being magnified4-fold by the traditional digital magnifier of FIG. 1;

FIG. 5 is a flowchart of a method for digitally magnifying imagesaccording to a preferred embodiment of the present invention;

FIG. 6 is a top view of the text image of FIG. 2 after being magnified2-fold by the method for digitally magnifying images according to thepreferred embodiment of the present invention; and

FIG. 7 is a top view of the text image of FIG. 2 after being magnified4-fold by the method for digitally magnifying images according to thepreferred embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention relates to a method for digitally magnifying (i.e.zooming) images applied to an electronic device comprising or connectedto an image capturing element. In a preferred embodiment of the presentinvention, the electronic device is preferably a mobile phone providedwith the image capturing element and a display screen, wherein the imagecapturing element is an image inputting apparatus used to captureimages, and the display screen is an image outputting apparatus used todisplay the images. As a result, when a user carries the mobile phone(i.e. the electronic device), the mobile phone can be used to real-timecapture the images via the image capturing element. Meanwhile, after theimage is magnified by the method of the present invention, the magnifiedimage can be directly displayed on the display screen of the mobilephone without adding any auxiliary hardware on the mobile phone. Inother words, the mobile phone (i.e. the electronic device) can be usedas an auxiliary reading tool to help visual impaired users for thepurpose of digitally magnifying images. However, the present inventionis not limited by the preferred embodiment of the mobile phone, and itis understood that the method of the present can also be applied tovarious electronic devices directly or indirectly installed with orconnected to the image capturing element (such as digital cameras,digital video cameras, PDAs, desktop computers, or notebook computers)invention for capturing, digitally magnifying, and displaying images, inorder to help users or other electronic devices to recognize or readfigures or texts.

Furthermore, when traditional electronic devices installed with orconnected to an image capturing element (such as mobile phones) are usedto preview images, there are various interference factors (such asvibrations of the mobile phones, uneven illumination, inaccuratefocusing, fuzziness, etc.). Thus, if the images are magnified accordingto a traditional bilinear interpolation amplification algorithm, theinterference factors will be magnified in proportion to the magnifiedratio of the images, so that the magnified images still fail to providebetter visual effect. As a result, according to the method of thepresent invention, when the electronic device is used to magnifyreal-time captured images, the present invention further providesadditional processes, such as a video stabilizing process, a noisesignal removing process, a fuzziness removing process, and a textstrengthening process. As a result, the method of the present inventioncan not only provide a function of a digital magnifier, but alsoefficiently reduce or remove various interference factors (such asvibrations, noise signals, uneven illumination, inaccurate focusing,fuzziness, etc.), so that the magnified text images will provide morestable and clearer visual effect. Referring now to FIG. 5, a flowchartof a method for digitally magnifying images according to a preferredembodiment of the present invention is illustrated. As shown, the methodis applied to the electronic device capable of executing digitallymagnifying processes to the preview images real-time inputted from theimage capturing element, wherein the digitally magnifying processes aredescribed more detailed as following.

In a step 200, an image capturing element real-time captures a pluralityof preview images;

In a step 201, a video stabilizing process is executed by calculatingthe motion of the image capturing element according to the plurality ofpreview images real-time captured by the image capturing element, andexecuting a fitting process to clear portions of the current previewimage and corresponding clear portions of a plurality of the previouspreview images, so as to efficiently remove the interference of randomnoise signals in the preview images caused by high-speed moving andvibrating of the image capturing element, for the purpose of providing amore stable and clearer preview image. According to the method of thepresent invention, the video stabilizing process is used to remove theinterference of random noise signals in the preview images caused byhigh-speed moving and vibrating of the image capturing element, but thevideo stabilizing process is not the only one feature of the presentinvention, while those skilled in the art can apparently understand thevideo stabilizing process, so that the detailed description thereof willbe omitted hereinafter.

In a step 202, a noise signal evaluating process is executed byautomatically scanning all pixels of each of the whole preview images,and executing a mathematical segmentation calculation to the pixels,wherein a portion of the pixels with the adjacent pixels having the samecolor thereto of the whole preview image will be defined as a segment,so that the whole preview image will be segmented into a plurality ofsegments. Then, executing a mathematical classification calculation toeach of the segments, wherein each of the segments will be merged withone of the adjacent segments having a minimum color difference,respectively, so as to segment each of the preview images into a textarea and a background area, in order to dynamically evaluate adistribution range of noise signals according to a segmentation resultof the text area and the background area. Generally, the variance of anormal text area is greater than that of a normal background area.Therefore, according to a preferred embodiment of the present invention,a means of dynamically evaluating the distribution range of noisesignals is preferably to calculate the variance of each of the pixels ofthe preview images within a predetermined area having a predeterminedsize, and then to compare the variance with a predetermined thresholdvalue. If the variance is greater than the predetermined thresholdvalue, the area belongs to a text area; and if the variance is smallerthan the predetermined threshold value, the area belongs to a backgroundarea. As a result, the present invention can efficiently segment each ofthe preview images into the text area and the background area. After thesegmentation of the text area and the background area is done, thestrength of noise signals in the text area can be defined as 0, and itis unnecessary to further execute a noise signal removing process to thetext area. On the other hand, the variance of the background area can beused as a parameter of the strength of noise signals in the backgroundarea;

In a step 203, executing an image magnifying process: according to themethod of the present invention, each of the preview images can bemagnified about 2-fold according to an anti-aliased fast doubleamplification algorithm, in order to prevent from the aliasing problemof edges of the texts. It should be noted that the preview image can bemagnified about 4-fold or more according to a gradually magnifyingtechnology of the present invention, i.e. the 4-fold preview image isgenerated by magnifying a pervious basis of the 2-fold preview image andsimultaneously executing a noise signal removing process, a fuzzinessremoving process, and a text strengthening process. Hence, themulti-fold magnified images processed by the method of the presentinvention can provide a visual effect more stable and clearer than thatof traditional magnified images that are directly magnified once.Generally, there are three types of traditional amplificationalgorithms:

(a) Nearest neighbor interpolation algorithm: it is a simplestinterpolation algorithm for magnifying pixels, wherein the color of eachpixel of a new image is selected from the color of one pixel which isnearest to an original pixel of an original image. For example, if theoriginal image is magnified about 200%, each one of original pixels willbe magnified into 4 new pixels having the same color to the originalpixel. Because the nearest neighbor interpolation algorithm may increasevisible sawtooth edges of the image, it is not practicable to magnifythe image by the interpolation algorithm;

(b) Bilinear interpolation algorithm: when using the bilinearinterpolation algorithm, the value of a pixel of a new image is selectedfrom the weighted average value of 4 pixels which are nearest to anoriginal pixel of an original image. Thus, the bilinear interpolationalgorithm is advantageous to create the image having smoother edgewithout visible sawtooth edges, for preventing from generating thevisible sawtooth edges; and

(c) Bicubic interpolation algorithm: it is a more complicatedinterpolation algorithm, wherein the value of a pixel of a new image isselected from the calculated value of 16 pixels which are nearest to anoriginal pixel of an original image. Thus, the bicubic interpolationalgorithm can not only provide higher accuracy, but also create theimage having smoother edges than that of the bilinear interpolationalgorithm. However, the bicubic interpolation algorithm needs more timeto calculate the pixel value.

According to the method of the present invention, the anti-aliased fastdouble amplification algorithm is used. It is an amplificationalgorithm, which is apparently faster than the bilinear interpolationalgorithm and can provide an amplification effect between the bilinearinterpolation algorithm and the bicubic interpolation algorithm. In apreferred embodiment of the present invention, the anti-aliased fastdouble amplification algorithm comprises the steps of: firstly executinga column interpolation algorithm, and then executing a row interpolationalgorithm, wherein the column interpolation algorithm is calculated asfollowing: each column of an original image is interpolated into doublenew columns:

one column of the original image: . . . p1, p2, p3, p4 . . .

one new column after interpolation: . . . q12,q21,q23,q32,q34,q43 . . .

Therein, the values of q12, q21, q23, q32, q34, and q43 are respectivelycalculated by the following equations:

q12=(p1*3+p2)/4;

q21=(p2*3+p1)/4;

q23=(p2*3+p3)/4;

q32=(p3*3+p2)/4;

q34=(p3*3+p4)/4; and

q43=(p4*3+p3)/4

Then, according to the same calculation rule, executing the columninterpolation algorithm to the last column and the next column of saidcolumn, respectively, so as to generate two new columns, respectively.Furthermore, according to the same calculation rule, finally executingthe row interpolation algorithm, so as to finish the 2-foldmagnification of the image. Because each pixel of the magnified image isinterpolated from 4 adjacent pixels of the original pixel of theoriginal image, it is advantageous to substantially reduce the sawtoothedges. Meanwhile, because the anti-aliased fast double amplificationalgorithm comprises the column interpolation algorithm and the rowinterpolation algorithm, both of which are respectively executed, it ispossible to simultaneously calculate a plurality of pixels according tothe storage characteristic of the image, in order to efficiently enhancethe magnification performance.

In a step 204, a noise signal removing process is executed. When thepresent invention executes the noise signal evaluating process, thepreview image is efficiently segmented into the text area and thebackground area, and the strength of noise signals in the text area isdefined as 0. Thus, when the noise signal removing process is executed,it is only necessary to the background area, and is unnecessary to thetext area. Thus, character points of the text area (such as the point ofEnglish letter “i”) can be efficiently protected from being removed.According to the method of the present invention, the noise signalremoving process is not the only feature of the present invention, whilethose skilled in the art can apparently understand the noise signalremoving process, so that the detailed description thereof will beomitted hereinafter.

In a step 205, a fuzziness removing process is executed. The previewimage is processed by a fuzzy kernel template according to a fastdeconvolution algorithm, in order to prevent from the fuzzy problem ofthe edges of the texts caused by inaccurately focusing of the imagecapturing element and magnifying the texts. Meanwhile, the fastdeconvolution algorithm is speeded up according to an integral imagemeans, so that the electronic device can provide a speed high enough toreal-time finish the image magnifying process. When the fuzzinessremoving process is applied to a mobile phone of Nokia 6620 installedwith a 32-bit RISC CPU (ARM-9, 150 MHz), the preview image can beprocessed up to a frame rate of 20 fps (frame per second). Generally, aconvolution process is a common method for processing the preview image,wherein an inputted image is processed into an outputted image having aplurality of pixels, each of which is selected from a weighted averagevalue of several pixels in a predetermined area of the imputed image.The weighted index of the weighted average value is defined by afunction which is called convolution kernel. Taking a mathematicalapplication as an example, if increasing the smoothness of a functionF(x) is desired, a common method is to execute a convolution process tothe original function F(x) and another function G(x), wherein thefunction G(x) is called the convolution kernel which is substantiallyequal to an integration process of the original function F(x). The fuzzykernel template of the present invention means a convolution kernel forexecuting a convolution process to the preview image, wherein theconvolution kernel may be a fuzzy kernel if the processed image is fuzzyafter finishing the convolution process, while a template correspondingto the fuzzy kernel is defined as a fuzzy kernel template. Generally, aconvolution procedure is similar to a multiplication procedure, while adeconvolution procedure is similar to a division procedure. Whenexecuting the division procedure once, repeated multiplicationprocedures are needed to achieve an approaching purpose. Meanwhile, thedetail calculation of the deconvolution procedure is also similar tothat of the division procedure, i.e. it needs repeated convolutionprocedures to calculate a deconvolution result. Taking a normalconvolution algorithm as an example, when executing a convolutionprocess to the preview image, each of pixels of the preview image willbe processed by calculating a product of several adjacent pixels in apredetermined area and a weighted index of the convolution kerneltemplate, and then adding all of the products. It is supposed that theconvolution kernel template is a Gaussian smoothing template asfollowing:

1/9 1/9 1/9 1/9 1/9 1/9 1/9 1/9 1/9

At this time, the convolution process needs to calculate the sum of theweighted values of the current pixel and 8 adjacent pixels, each ofwhich are multiplied by the weighted index 1/9, respectively. Asdescribed above, the larger the convolution kernel template becomes, themore calculations the convolution process comprises. Equally, thedeconvolution process will have more calculations. In view of theforegoing problem, the present invention uses the integral imagetechnology for speeding up the fast deconvolution algorithm. As aresult, if a predetermined area is square, it only needs 4 times ofaddition calculations to calculate the sum of all pixels in thepredetermined square area, so as to efficiently solve the loadingproblem of calculating the sum of the predetermined area. In a preferredembodiment of the present invention, the fuzzy kernel template islimited to an average template, wherein all weighted values in the fuzzykernel template are the same. Thus, when calculating the convolution, itonly needs to add all pixels in the predetermined area and execute theintegral image technology, to substantially enhance the convolutionspeed. Similarly, the deconvolution speed will be substantiallyenhanced, too.

In a step 206, a partial text strengthening process is executed Thepreview image is efficiently segmented into the text area and thebackground according to a peripherally statistic data of a text, and thetext area is correspondingly strengthened based on a dynamic thresholdvalue, so that a text content of the preview image inputted after beingmagnified 2-fold will be sharper and the edges of the texts will besmoother. According to the present invention, the dynamic thresholdvalue is commonly constructed by a mean variance of a gray value of thecurrent pixel of the preview image and an average gray value of severalpixels adjacent to the current pixel in a predetermined area. Theforegoing parameters are used to adjust iteration times and a strengthindex of the deconvolution, so as to carry out a clear and sharp effectof texts. Furthermore, according to the difference between the currentgray value and the average gray value, a probability value of thecurrent pixel in relation to the adjacent pixels in the predeterminedarea can be calculated. Then, the probability value can be used as aweighted index to adjust the brightness of the current pixel, so as toachieve the purpose of smoothening the edges of the texts.

In a step 207, whether the preview image is magnified up to apredetermined amplification factor set by a user is determined. If yes,the procedure goes to a step 208; and if no, it goes back to the step203 to re-execute the 2-fold image magnifying process to the previewimage, and then execute the noise signal removing process, the fuzzinessremoving process, and the partial text strengthening process, in orderto generate a preview image magnified about 4-fold or more.

In a step 208, the preview image after being magnified is outputted to adisplay screen for displaying the preview image. As a result, the methodof the present invention can not only provide a function of a digitalmagnifier, but also efficiently reduce or remove various interferencefactors (such as vibrations, noise signals, uneven illumination,inaccurate focusing, fuzziness, etc.), so that the magnified images willprovide more stable and clearer visual effect.

As described above, the present invention has been described with theforegoing preferred embodiment thereof and it is understood that manychanges and modifications to the described embodiment can be carried outwithout departing from the scope and the spirit of the invention. Forexample, when the preview image is magnified about 4-fold or more, stepsof the foregoing processes can be increased, deleted, or adjusted, onlyif the processes can magnify the preview image about 4-fold or moreaccording to a gradually magnifying technology, i.e. the 4-fold previewimage is generated by magnifying a pervious basis of the 2-fold previewimage and simultaneously executing the fuzziness removing process andthe text strengthening process.

In the preferred embodiment of the present invention, the electronicdevice is used as a digital magnifier which can collect text data ofnewspapers, magazines, books, or letters via an image capturing elementthereof, and then magnify the text data followed by displaying the textdata on a display screen of the electronic device for a user to read. Incomparison with a traditional digital magnifier calculated according tothe bilinear interpolation algorithm, the traditional digital magnifieris used to magnify the text data as shown in FIG. 2 about 2-fold, so asto generate a magnified image as shown in FIG. 3. In addition, themagnified image can be also magnified 4-fold into a magnified image asshown in FIG. 4. Referring to the magnified images of FIGS. 3 and 4, itshould be noted that the preview image includes more noise signals, andthe edges of the texts are fuzzier. On the contrary, the method of thepresent invention can be used to magnify the text data as shown in FIG.2 about 2-fold and 4-fold in turn, in order to generate a 2-foldmagnified image as shown in FIG. 6 and a 4-fold magnified image as shownin FIG. 7 in turn, wherein the preview image only includes fewer noisesignals for providing more stable and clearer text effect. Therefore, ifthe middle ages and old ages having the presbyopic problem can carry theelectronic device of the present invention (such as a mobile phone, adigital camera, or a PDA), the electronic device can be used as adigital magnifier for reading newspapers, magazines, books, or letters,in order to carry out a function of a physical magnifier, so that itwill be unnecessary for them to additionally carry the presbyopicglasses (i.e. reading glasses) or the magnifier.

In alternatively preferred embodiments of the present invention, theelectronic device can be further installed with other traditionalcharacter recognition software selected from the group consisting ofoptical character recognition (OCR) software, bar code recognition (BCR)software, and business card recognition (Biz card) software. Thus, inoperation, the electronic device can be firstly used to digitallymagnify the content of texts or bar codes in an inputted image andremove noise signals therein according to the method of the presentinvention, and then the magnified image can be outputted to one of thecharacter recognition software for recognizing the texts or the barcodes, so as to efficiently enhance the recognition capacity of thecharacter recognition software. Moreover, the method of the presentinvention can be used as a software development kit (SDK) which can beapplied to various electronic devices installed with various characterrecognition software of OCR, BCR, or Biz Card, so as to carry out afunction of recognizing and reading the image or texts when it isnecessary to magnify texts, bar codes, and symbols in related fields byfollowing means:

(1) The method of the present invention can obtain data of newspapers ormagazines via the image capturing element, and then output the data bylinking to a computer via a data cable, in order to display themagnified data on a computer display. Although the foregoing operationmode can not be always carried out anywhere at any time, it is easierfor a user to obtain more content with a higher amplification factor dueto the computer display is apparently greater than a display screen of anormal mobile phone. Thus, the foregoing operation mode is suitable forthe user to read the data in office or home, and the cost thereof issubstantially lower than that of the traditional digital magnifier, suchas the digital magnifier as shown in FIG. 1;

(2) The method of the present invention can be used as a SDK: the methodand one traditional character recognition software (such as OCR, BCR, orBiz card software) can be commonly installed into a portable electronicdevice (such as a mobile phone, a digital camera, or a PDA), wherein themethod of the present invention is defined as a pre-processing softwareto provide a clear image with enough resolution to be recognized beforecarrying out the traditional character recognition software, so as toenhance the success rate of character recognition;

(3) The method of the present invention can be used to magnify charactertemplates of a mobile phone: because some types of mobile phones onlyprovide a limited storage capacity, some character templates can not bestored as a vector diagram or a high-resolution bitmap (BMP). At thistime, the method for digitally magnifying images according to thepresent invention can be used to magnify and process low-resolutioncharacter templates into high-resolution character templates, so as toefficiently save the storage space of the mobile phone and provide morecharacters with various sizes for use;

(4) The method of the present invention can be used to magnify a frameof a display screen: it is similar to a magnifier function of Windowssystem, but can provide a better magnifier effect than that of theWindows system. Especially, the magnified texts will be clearer andeasier to be read, so that the method of the present invention canprovide a better magnified visual effect than that of the Windows systemfor a computer user who needs to use the magnifier function; and

(5) The method of the present invention can be used to magnifysubtitles:

for a special application of magnifying the frame of the display screen,such as seeing a movie displayed on the display screen, the method fordigitally magnifying images according to the present invention can beused to partially magnify the subtitles of the movie, so that the userwith poor eyesight still can read the subtitles at a relatively longdistance.

The present invention has been described with a preferred embodimentthereof and it is understood that many changes and modifications to thedescribed embodiment can be carried out without departing from the scopeand the spirit of the invention that is intended to be limited only bythe appended claims.

1. A method for digitally magnifying images applied to an electronicdevice, comprising: reading in a preview image inputted into theelectronic device; executing a 2-fold image magnifying process to thepreview image; executing a fuzziness removing process to the previewimage; segmenting the preview image into a background area and a textarea, and executing a correspondingly text strengthening process to thetext area; and determining whether the preview image is magnified up toa predetermined amplification factor; when yes, outputting the previewimage after being magnified to a display screen for displaying thepreview image; otherwise, going back to re-execute the 2-fold imagemagnifying process to the magnified preview image, and then executingthe fuzziness removing process and the text strengthening process, inorder to generate the preview image magnified about 4-fold or more. 2.The method for digitally magnifying images of claim 1, wherein thefuzziness removing process is executed by processing the preview imageby a fuzzy kernel template according to a fast deconvolution algorithm.3. The method for digitally magnifying images of claim 1, wherein thetext strengthening process is executed by correspondingly strengtheningthe text area based on a dynamic threshold value which is commonlyconstructed by a mean variance of a gray value of a current pixel of thepreview image and an average gray value of several pixels adjacent tothe current pixel in a predetermined area, so that the dynamic thresholdvalue is used to calculate a probability value of the current pixel inrelation to the adjacent pixels in the predetermined area, while theprobability value is used as a weighted index to adjust the brightnessof the current pixel for correspondingly strengthening the text area. 4.The method for digitally magnifying images of claim 1, furthercomprising: a noise signal evaluating process for segmenting the previewimage into the text area and the background area, in order todynamically evaluate a distribution range of noise signals according toa segmentation result of the text area and the background area, whereina means of dynamically evaluating the distribution range of noisesignals is to calculate a variance of each of the pixels of the previewimages within a predetermined area, and then to compare the variancewith a predetermined threshold value; when the variance is greater thanthe predetermined threshold value, the area belongs to the text area;and when the variance is smaller than the predetermined threshold value,the area belongs to the background area; after segmenting the previewimages into the text area and the background area, the strength of noisesignals in the text area is defined as 0, and the variance of thebackground area is used as a parameter of the strength of noise signalsin the background area; and a noise signal removing process for removingnoise signals in the background area.
 5. The method for digitallymagnifying images of claim 1, wherein the 2-fold image magnifyingprocess of the preview image is executed according to an anti-aliasedfast double amplification algorithm which comprises a columninterpolation algorithm and a row interpolation algorithm, wherein eachcolumn of an original preview image is interpolated into double newcolumns according to the column interpolation algorithm, while each rowof an original preview image is interpolated into double new rowsaccording to the row interpolation algorithm; and then the columninterpolation algorithm is executed to the last column and the nextcolumn of said column, respectively, to generate two corresponding newcolumns, respectively, while the row interpolation algorithm is executedto the last row and the next row of said row, respectively, to generatetwo corresponding new rows, respectively; so that the 2-fold imagemagnifying process of the preview image is finished.
 6. The method fordigitally magnifying images of claim 2, wherein the 2-fold imagemagnifying process of the preview image is executed according to ananti-aliased fast double amplification algorithm which comprises acolumn interpolation algorithm and a row interpolation algorithm,wherein each column of an original preview image is interpolated intodouble new columns according to the column interpolation algorithm,while each row of an original preview image is interpolated into doublenew rows according to the row interpolation algorithm; and then thecolumn interpolation algorithm is executed to the last column and thenext column of said column, respectively, to generate two correspondingnew columns, respectively, while the row interpolation algorithm isexecuted to the last row and the next row of said row, respectively, togenerate two corresponding new rows, respectively; so that the 2-foldimage magnifying process of the preview image is finished.
 7. The methodfor digitally magnifying images of claim 3, wherein the 2-fold imagemagnifying process of the preview image is executed according to ananti-aliased fast double amplification algorithm which comprises acolumn interpolation algorithm and a row interpolation algorithm,wherein each column of an original preview image is interpolated intodouble new columns according to the column interpolation algorithm,while each row of an original preview image is interpolated into doublenew rows according to the row interpolation algorithm; and then thecolumn interpolation algorithm is executed to the last column and thenext column of said column, respectively, to generate two correspondingnew columns, respectively, while the row interpolation algorithm isexecuted to the last row and the next row of said row, respectively, togenerate two corresponding new rows, respectively; so that the 2-foldimage magnifying process of the preview image is finished.
 8. The methodfor digitally magnifying images of claim 4, wherein the 2-fold imagemagnifying process of the preview image is executed according to ananti-aliased fast double amplification algorithm which comprises acolumn interpolation algorithm and a row interpolation algorithm,wherein each column of an original preview image is interpolated intodouble new columns according to the column interpolation algorithm,while each row of an original preview image is interpolated into doublenew rows according to the row interpolation algorithm; and then thecolumn interpolation algorithm is executed to the last column and thenext column of said column, respectively, to generate two correspondingnew columns, respectively, while the row interpolation algorithm isexecuted to the last row and the next row of said row, respectively, togenerate two corresponding new rows, respectively; so that the 2-foldimage magnifying process of the preview image is finished.
 9. The methodfor digitally magnifying images of claim 5, further comprising anintegral image technology to speed up the fast deconvolution algorithm,wherein the fast deconvolution algorithm is used to process the previewimage by a predetermined fuzzy kernel template, and the integral imagetechnology is used to speed up the fast deconvolution algorithm.
 10. Themethod for digitally magnifying images of claim 6, further comprising anintegral image technology to speed up the fast deconvolution algorithm,wherein the fast deconvolution algorithm is used to process the previewimage by a predetermined fuzzy kernel template, and the integral imagetechnology is used to speed up the fast deconvolution algorithm.
 11. Themethod for digitally magnifying images of claim 7, further comprising anintegral image technology to speed up the fast deconvolution algorithm,wherein the fast deconvolution algorithm is used to process the previewimage by a predetermined fuzzy kernel template, and the integral imagetechnology is used to speed up the fast deconvolution algorithm.
 12. Themethod for digitally magnifying images of claim 8, further comprising anintegral image technology to speed up the fast deconvolution algorithm,wherein the fast deconvolution algorithm is used to process the previewimage by a predetermined fuzzy kernel template, and the integral imagetechnology is used to speed up the fast deconvolution algorithm.
 13. Themethod for digitally magnifying images of claim 9, wherein the fuzzykernel template is an average template and all weighted values in thefuzzy kernel template are the same.
 14. The method for digitallymagnifying images of claim 10, wherein the fuzzy kernel template is anaverage template and all weighted values in the fuzzy kernel templateare the same.
 15. The method for digitally magnifying images of claim11, wherein the fuzzy kernel template is an average template and allweighted values in the fuzzy kernel template are the same.
 16. Themethod for digitally magnifying images of claim 12, wherein the fuzzykernel template is an average template and all weighted values in thefuzzy kernel template are the same.
 17. A method for digitallymagnifying images applied to an electronic device, comprising: readingin a plurality of preview images real-time inputted into the electronicdevice; calculating a motion of an image capturing element according tothe plurality of preview images real-time inputted, and executing afitting process to clear portions of a current preview image andcorresponding clear portions of a plurality of previous preview images,so as to remove an interference of random noise signals in the previewimages caused by high-speed moving and vibrating of the image capturingelement, for providing a preview image processed by the fitting process;executing a 2-fold image magnifying process to the preview image;executing a fuzziness removing process to the preview image; segmentingthe preview image processed by the fitting process into a backgroundarea and a text area, and executing a correspondingly text strengtheningprocess to the text area; and determining whether the preview imageprocessed by the fitting process is magnified up to a predeterminedamplification factor; when yes, outputting the preview image after beingmagnified to a display screen for displaying the preview image; andotherwise, going back to re-execute the 2-fold image magnifying processto the magnified preview image, and then executing the fuzzinessremoving process and the text strengthening process, in order togenerate the preview image magnified about 4-fold or more.
 18. Themethod for digitally magnifying images of claim 17, wherein thefuzziness removing process is executed by processing the preview imageby a fuzzy kernel template according to a fast deconvolution algorithm.19. The method for digitally magnifying images of claim 17, wherein thetext strengthening process is executed by correspondingly strengtheningthe text area based on a dynamic threshold value which is commonlyconstructed by a mean variance of a gray value of a current pixel of thepreview image and an average gray value of several pixels adjacent tothe current pixel in a predetermined area, so that the dynamic thresholdvalue is used to calculate a probability value of the current pixel inrelation to the adjacent pixels in the predetermined area, while theprobability value is used as a weighted index to adjust the brightnessof the current pixel for correspondingly strengthening the text area.20. The method for digitally magnifying images of claim 17, furthercomprising: a noise signal evaluating process for segmenting the previewimage into the text area and the background area, in order todynamically evaluate a distribution range of noise signals according toa segmentation result of the text area and the background area, whereina means of dynamically evaluating the distribution range of noisesignals is to calculate a variance of each of the pixels of the previewimages within a predetermined area, and then to compare the variancewith a predetermined threshold value; when the variance is greater thanthe predetermined threshold value, the area belongs to the text area;and when the variance is smaller than the predetermined threshold value,the area belongs to the background area; after segmenting the previewimages into the text area and the background area, the strength of noisesignals in the text area is defined as 0, and the variance of thebackground area is used as a parameter of the strength of noise signalsin the background area; and a noise signal removing process for removingnoise signals in the background area.
 21. The method for digitallymagnifying images of claim 17, wherein the 2-fold image magnifyingprocess of the preview image is executed according to an anti-aliasedfast double amplification algorithm which comprises a columninterpolation algorithm and a row interpolation algorithm, wherein eachcolumn of an original preview image is interpolated into double newcolumns according to the column interpolation algorithm, while each rowof an original preview image is interpolated into double new rowsaccording to the row interpolation algorithm; and then the columninterpolation algorithm is executed to the last column and the nextcolumn of said column, respectively, to generate two corresponding newcolumns, respectively, while the row interpolation algorithm is executedto the last row and the next row of said row, respectively, to generatetwo corresponding new rows, respectively; so that the 2-fold imagemagnifying process of the preview image is finished.
 22. The method fordigitally magnifying images of claim 18, wherein the 2-fold imagemagnifying process of the preview image is executed according to ananti-aliased fast double amplification algorithm which comprises acolumn interpolation algorithm and a row interpolation algorithm,wherein each column of an original preview image is interpolated intodouble new columns according to the column interpolation algorithm,while each row of an original preview image is interpolated into doublenew rows according to the row interpolation algorithm; and then thecolumn interpolation algorithm is executed to the last column and thenext column of said column, respectively, to generate two correspondingnew columns, respectively, while the row interpolation algorithm isexecuted to the last row and the next row of said row, respectively, togenerate two corresponding new rows, respectively; so that the 2-foldimage magnifying process of the preview image is finished.
 23. Themethod for digitally magnifying images of claim 19, wherein the 2-foldimage magnifying process of the preview image is executed according toan anti-aliased fast double amplification algorithm which comprises acolumn interpolation algorithm and a row interpolation algorithm,wherein each column of an original preview image is interpolated intodouble new columns according to the column interpolation algorithm,while each row of an original preview image is interpolated into doublenew rows according to the row interpolation algorithm; and then thecolumn interpolation algorithm is executed to the last column and thenext column of said column, respectively, to generate two correspondingnew columns, respectively, while the row interpolation algorithm isexecuted to the last row and the next row of said row, respectively, togenerate two corresponding new rows, respectively; so that the 2-foldimage magnifying process of the preview image is finished.
 24. Themethod for digitally magnifying images of claim 20, wherein the 2-foldimage magnifying process of the preview image is executed according toan anti-aliased fast double amplification algorithm which comprises acolumn interpolation algorithm and a row interpolation algorithm,wherein each column of an original preview image is interpolated intodouble new columns according to the column interpolation algorithm,while each row of an original preview image is interpolated into doublenew rows according to the row interpolation algorithm; and then thecolumn interpolation algorithm is executed to the last column and thenext column of said column, respectively, to generate two correspondingnew columns, respectively, while the row interpolation algorithm isexecuted to the last row and the next row of said row, respectively, togenerate two corresponding new rows, respectively; so that the 2-foldimage magnifying process of the preview image is finished.
 25. Themethod for digitally magnifying images of claim 21, further comprisingan integral image technology to speed up the fast deconvolutionalgorithm, wherein the fast deconvolution algorithm is used to processthe preview image by a predetermined fuzzy kernel template, and theintegral image technology is used to speed up the fast deconvolutionalgorithm.
 26. The method for digitally magnifying images of claim 22,further comprising an integral image technology to speed up the fastdeconvolution algorithm, wherein the fast deconvolution algorithm isused to process the preview image by a predetermined fuzzy kerneltemplate, and the integral image technology is used to speed up the fastdeconvolution algorithm.
 27. The method for digitally magnifying imagesof claim 23, further comprising an integral image technology to speed upthe fast deconvolution algorithm, wherein the fast deconvolutionalgorithm is used to process the preview image by a predetermined fuzzykernel template, and the integral image technology is used to speed upthe fast deconvolution algorithm.
 28. The method for digitallymagnifying images of claim 24, further comprising an integral imagetechnology to speed up the fast deconvolution algorithm, wherein thefast deconvolution algorithm is used to process the preview image by apredetermined fuzzy kernel template, and the integral image technologyis used to speed up the fast deconvolution algorithm.
 29. The method fordigitally magnifying images of claim 25, wherein the fuzzy kerneltemplate is an average template, wherein all weighted values in thefuzzy kernel template are the same.
 30. The method for digitallymagnifying images of claim 26, wherein the fuzzy kernel template is anaverage template, wherein all weighted values in the fuzzy kerneltemplate are the same.
 31. The method for digitally magnifying images ofclaim 27, wherein the fuzzy kernel template is an average template,wherein all weighted values in the fuzzy kernel template are the same.32. The method for digitally magnifying images of claim 28, wherein thefuzzy kernel template is an average template, wherein all weightedvalues in the fuzzy kernel template are the same.